In the transit-only scenarios, expanded transit services tend to increase transit shares (median = 6%, N = 11) and reduce automobile and non-motorized shares (median = –0.8%, N = 11; median = –0.6%, N = 9, respectively) (see Figures 3, 4, and 5). Non-motorized shares may decrease when improved service makes transit more competitive with walking and biking in terms of travel time and cost. Except in the Brussels study, congestion (VHD) and travel time are reduced in transit-only scenarios (median = –1.9%, N = 8; median = –1.8%, N = 8, respectively). In Brussels, the simulation of improved transit service with a land-use model increased land consumption and decreased density, which tends to increase trip lengths and overall travel times.208 Not surprisingly, access to the city center and services, as measured in the EU studies, also improves (median = 1.4%; median =
0.6%, N = 6, respectively), except in Brussels.209 Accessibility measures, as measured in
the UK and San Francisco studies, most typically show increases in transit access and reductions in automobile access to destination, locations, and services (Table 11 shows accessibility performance measures implemented by destination type, policy type, and mode/time criteria).210
In the land-use-only scenarios, as densities increase, activity origins and destinations are closer together, and transportation performance measures indicate that more trips are made by non-motorized modes and transit and fewer trips are made by automobile (see Figures 3, 4, and 5). In San Francisco, the automobile mode share is reduced by 1%, transit is increased by 7%, and walking and bicycling are increased by 10% and 13%,
respectively.211 In Washington, DC, automobile trips decline by less than 1%, and transit
and non-motorized trips increase by 1% to 5%.212 As automobile travel declines, congestion may also be reduced, as reported in scenarios in San Francisco (–37%), Philadelphia
38 Evidence for Performance Measures
(–14%), and Orlando (–9%).213 Total vehicle hours of travel decline in Orlando (–5%), and
average daily and peak vehicle speeds increase in Washington, DC, and Austin.214
In the land-use and transit studies, increases in density and expanded transit promote transit and non-motorized travel (median = 50%, N = 19; median = 11%, N = 18, respectively) and reduce automobile travel (median = 3%, N = 23). The greatest increases in transit and non-motorized shares are reported in Sacramento, where baselines are low, as well as in
visioning and advanced studies.215 For transit, MTP values range from 4% to 111%, and
the remaining visioning studies report values from 0% to 150%. For non-motorized modes, MTP values range from –20% to 15%, remaining visioning studies range from –9% to 125%, and advanced studies range from –7% to 17%. Negative values indicate a shift from non-motorized to transit modes. The greatest reductions occur in visioning studies from Chicago (–16%) and Sacramento (–11%), while MTPs report reductions of 0.3% to 7%, the remaining visioning studies report reductions of 0.3% to 8%, and the academic/ international studies report reductions of 2% to 8%.216
As automobile use decreases in land-use and transit scenarios, average travel time declines (median = 14%, N = 15). MTPs report values near the median, while values from visioning studies range from 25% in Sacramento to 2% in Salt Lake City.217 As travel times decrease, so does congestion, as measured by VHD (median = 27%, N = 24). Studies in Chicago report the greatest decrease (68%), while Sacramento’s academic studies report the least change (3%).218
Accessibility measures relative to travel-time criteria are reported in the land-use and
transit scenarios in the Los Angeles and San Diego MTPs.219 Los Angeles measures accessibility through the change in “accessible jobs” (those within 45 minutes travel time) by automobile (–3%) and transit (10%). San Diego’s MTP reports a 3% increase in work and higher-education trips accessible within 30 minutes.
Parking pricing scenarios in the studies reviewed tend to decrease automobile mode
share (median = –2.12%, high = –4.97%, low = –0.36%, N = 14) and increase transit (N = 12) and non-motorized (N = 10) mode shares (median = 1.7%). VHD and travel time also tend to decrease in these studies (median = –2.29%, N = 20; median = –1.5%, N = 20, respectively). The exceptions are the EU cities of Bilbao, Vincenza, and Naples, in which parking pricing studies are simulated with a land-use model and show reductions
in employment (10% to 0.5%) and population (8% to 0.4%) in their city centers.220 As a
result, Bilbao experiences a decline in transit mode share, Vincenza see declines in non- motorized mode share and increases in VHD, and Naples experiences increases in travel
times. In California, regional scenarios show reductions in VHD ranging from 9% to 2%.221
39 Evidence for Performance Measures
Figure 3. Transit Mode Share222 (N = 94)
40 Evidence for Performance Measures
Figure 5. Non-Motorized Mode Share224 (N = 94)
41 Evidence for Performance Measures
Figure 7. Travel Time226 (N = 136)
42 Evidence for Performance Measures
43 Evidence for Performance Measures
Table 11. Accessibility Performance Measures
Destination Mode Time Criteria (Minutes) Percentage Change (%) Policy Type
All destinations All — -1.0 to 0.9 Pricing and transit229
CBD/activity center All — -22.4 to -12.1 Pricing and transit
230
10 6.6 Land-use231
Employment
All
— -3.8 to -2.7 Pricing and transit232
20 -1.2 Transit233
40 0.0 Transit234
Auto
15 1.3 Land-use/transit235
30 -0.3 to 0.7 Pricing and transit, transit236
45 0.2 to 2.7 Land-use/transit237 Transit 15 22.2 Land-use/transit238 30 11.0 to 13.9 Transit, land-use/transit239 45 7.0 to 10.0 Land-use/transit240 Shopping
All - -2.5 to -1.8 Pricing and transit241
Auto 15 -0.7 Transit242
Transit 15 19.1 Transit243
Retail purchasing power All - -2.9 to -2.0 Pricing and transit244
Supermarket All 15 -1.2 Transit
245
30 0.0 Transit246
General practitioner All 15 0.0 Transit
247
30 0.0 Transit248
Primary school All 15 -1.0 Transit
249
30 0.0 Transit250
Secondary school All
- -3.9 to -2.8 Pricing and transit251
20 1.0 Transit252
40 1.0 Transit253
Further education All 30 1.0 to 3.1 Pricing and transit, transit
254
60 1.0 Transit255
Intermodal station All 5 8.3 Land-use256
International airport All 30 12.1 Land-use257
44 Evidence for Performance Measures
Cordon pricing in the EU regions tends to reduce regional automobile mode share (median
= –1.2%, N = 12) and increase demand for lower-cost transit (median = 1%, N = 12) and
non-motorized travel modes (median = 0.5%, N = 10).259 VHD and travel times also tend
to decline (median = –2.6%, N = 18; median = –0.4%, N = 12), while accessibility to the city center and services generally increase (center median = –1.7%; services median = –0.8%, N = 12). The exceptions to these trends are related to the land-use effects of the cordon pricing scenarios simulated with land-use models. The cordon tolls result in the decentralization of population and employment in both Naples and Dortmund. The opposite is true in Bilbao. There is a slight decrease in non-motorized modes share in Naples, and in Dortmund, VHD is increased and accessibility is decreased. Travel time for all modes increases in Bilbao, Dortmund, and Naples.
Travel performance measures for congestion pricing scenarios are limited to travel time and VHD. Median travel time decreases for all California scenarios (N = 4) by 7% (high =
–10%, low = –5%).260 As travel time decreases, so does congestion: the Washington, DC,
and California scenarios show a median reduction in VHD of 26% (N = 8) and a median
reduction in range of –64% to –17%.261
In the VMT pricing policy scenarios, as vehicle operating costs increase, automobile mode shares decrease (median = –3%, N = 22) and transit and non-motorized mode shares
increase (median = 2% and 3%, respectively, N = 22) in the EU regions and Sacramento.262
Travel time in the EU regions declines (median = –6.6%; N = 21), as does VHD in the EU
regions, California, and Washington, DC (median = –6.6%, N = 27).263 VHD reductions for
California range from –11% to –8%; for Washington, DC, they range from –41% to –28%; and for EU regions, they range from –13% to –0.5%. Accessibility increases in all the EU regions (center median = –2.9%; services median = –3.4%, N = 21).
In the fuel pricing studies, vehicle operating costs increase and vary by the fuel efficiency of individual vehicles; thus, automobile mode shares decline. For example, in Washington,
DC, automobile mode share decreases by 2%.264 Travel time and VHD are also reduced
(travel time median = 12%, VHD median = 18%, N = 17). The California-regions scenario simulates increases in fuel prices that are higher relative to the VMT pricing charges, which helps explain the larger median percentage change in travel time and VHD (see Figures 6 and 7).265
Emissions pricing scenarios in the California regions include travel time and VHD.266 Travel time is reduced in all scenarios by a median of 3% (high = –4%, low = –2, N = 8). VHD is also reduced in all scenarios by a median of 4% (high = –6%, low = –3%, N = 8).
A limited number of studies include combined pricing scenarios. The San Francisco visioning study and the advanced Sacramento study show decreases in automobile ownership ranging from 1% to 5% and increases in transit mode share (approximately
30%) and non-motorized mode share.267 Not surprisingly, given the magnitude of the policy
change, all studies show significant reductions in travel time and VHD (median = 19%, N = 9; median = 40%, N = 10, respectively).
45 Evidence for Performance Measures
In the pricing and transit studies, automobile mode share tends to decrease in all locations (median = 9%, N = 13), while transit and non-motorized mode shares tend to increase (median = 21%, N = 14; median = 1%, N = 12, respectively). Travel time is generally reduced (median = –1%, N = 10); however, results for VHD are mixed (median = 2%, N = 7, respectively). In Edinburgh, Helsinki, Dortmund, and Naples, the pricing and
transit scenarios are simulated with a land-use model.268 Decentralized housing and/or
employment resulting from the pricing and transit policies decreases transit and non- motorized mode shares in Edinburgh, decreases non-motorized modes in Helsinki and Naples, increases travel time in Naples and Dortmund, and increases VHD in Helsinki and Naples. A UK study measures accessibility through change in population within given travel times to employment, supermarket, general practitioner, primary school, and secondary
school and finds percentage changes ranging from –1% to 1%.269
Combined pricing, land-use, and transit studies show reductions in automobile mode
share (median = 10%, N = 16) and increases in transit and non-motorized mode share (median = 52% and 37%, respectively, N = 29). The exceptions to these trends are found in Helsinki, Dortmund, and Naples, where the pricing and transit scenarios are simulated with a land-use model, and land-use changes result in decreases in non-motorized mode
share and increases in travel time and VHD.270 Scenarios in Dortmund measure change in
overall accessibility of population and accessibility of employment, shops, retail purchasing power, high schools, and CBD, with percentage changes ranging from –39% to –1%.